Orca 2 enhances small language models' reasoning by teaching diverse strategies for tasks, outperforming models up to 10x larger in complex benchmarks.
Authors: Arindam Mitra; Luciano Del Corro, work done while at Microsoft; Shweti Mahajan, work done while at Microsoft; Andres Codas, denote equal contributions; Clarisse Simoes, denote equal contributions; Sahaj Agarwal; Xuxi Chen, work done while at Microsoft;; Anastasia Razdaibiedina, work done while at Microsoft; Erik Jones, work done while at Microsoft; Kriti Aggarwal, work done while at Microsoft; Hamid Palangi; Guoqing Zheng; Corby Rosset; Hamed Khanpour; Ahmed Awadall.
Eval is a collection of diverse sets of standardized tests including general college admission tests like the GRE, GMAT, and SAT; law-focused examinations such as the LSAT and lawyer qualification assessments; math competitions; and national civil service examinations .
Eval :
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Orca 2: Enhancing Reasoning in Smaller Language Models - Abstract and IntroductionOrca 2 enhances small language models' reasoning by teaching diverse strategies for tasks, outperforming models up to 10x larger in complex benchmarks.
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Orca 2: Enhancing Reasoning in Smaller Language ModelsOrca 2 enhances small language models' reasoning by teaching diverse strategies for tasks, outperforming models up to 10x larger in complex benchmarks.
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Orca 2: Enhancing Reasoning in Smaller Language ModelsOrca 2 enhances small language models' reasoning by teaching diverse strategies for tasks, outperforming models up to 10x larger in complex benchmarks.
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Orca 2: Enhancing Reasoning in Smaller Language ModelsOrca 2 enhances small language models' reasoning by teaching diverse strategies for tasks, outperforming models up to 10x larger in complex benchmarks.
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